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Seminar announcement
by Marco Scarsini 30 Apr '21

30 Apr '21

Thursday, 5 May, 17:00 CEST *Marta Blangiardo,* Imperial College Estimating Weekly Excess Mortality at Sub-National Level in Italy during the COVID-19 Pandemic <http://mailsender.luiss.it/lists/lt.php?id=cRpQBAcGSAULAwdOVgFdBQs> Discussants: Marcus Ebeling and Javier Rubio This is the link to the Virtual Room <http://mailsender.luiss.it/lists/lt.php?id=cRpQAAYBSAULAwdOVgFdBQs>. If you want to receive the password to access the virtual room, please fill out this form <https://docs.google.com/forms/d/e/1FAIpQLSeDxM-M5ogG43elgjC-lNCp0BDhISiZHG0…> (If you filled it out in the past, this is not necessary). The schedule of the upcoming seminars can be found here <https://economiaefinanza.luiss.it/en/seminars/2020-2021-seminars>. ******************************************************* Marco Scarsini Dipartimento di Economia e Finanza Luiss Viale Romania 32 00197 Roma, ITALY URL: http://docenti.luiss.it/scarsini/

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Fwd: Post-Doc position at the University of Basel
by Francesco Caravenna 30 Apr '21

30 Apr '21

Ricevo e inoltro. > Da: David Belius <david.belius(a)unibas.ch> > Oggetto: Post-Doc position at the University of Basel > Data: 22 aprile 2021 14:39:55 CEST > > Dear Colleagues, > > I am looking to fill a Post-Doc position at the University of Basel in Switzerland funded by my Swiss National Science Foundation Project "Hierarchical Structure and the Extrema of Correlated Random Fields". The candidate will work with myself, my group and my collaborators on high dimensional statistical physics problems such as the Sherrington-Kirkpatrick and related models. Topics will include critical point complexity and the development of a mathematically rigorous TAP approach. > > The starting date is 1 September 2021 (there is a bit of flexibility) with a planned duration of two years. Candidates should contact me by e-mail with a CV. Please forward this e-mail to anyone you think may be interested, and feel free to contact me about potential candidates directly. > > Best Regards, > David Belius > > -- > _______________________________ > David Belius | SNF Professor > Department of Mathematics and Computer Science | University of Basel > david.belius(a)unibas.ch <mailto:david.belius@unibas.ch> | +41 61 207 55 82 | Spiegelgasse 1, 4051 Basel, Switzerland > https://probability.dmi.unibas.ch/belius <https://probability.dmi.unibas.ch/belius>

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Corso on Frequency domain approach to time series analysis
by Elvira Di Nardo 30 Apr '21

30 Apr '21

Cari colleghi, nell’ambito del programma di Visiting Professors della Laurea Magistrale in Stochastics and Data Science dell’Università di Torino (programma completo alla pagina https://www.master-sds.unito.it/go/visiting), verrà svolto il seguente corso on-line: -------------------------------------- Luis Alberiko Gil-Alana (University of Navarra, Spain) A FREQUENCY DOMAIN COURSE ON TIME SERIES ANALYSIS This course deals with the analysis of time series. After a short review in the time domain, focusing on aspects such as autocovariances, estimation, testing, Box-Jenkins methodology, seasonality, prediction and non-stationary issues, the course will focus on the frequency domain, introducing the spectral distribution function or spectrum along with the spectral density function, the periodogram and other issues such as long memory processes. -------------------------------------- Il corso si svolgerà online secondo il seguente calendario - mar 4 Maggio, h.11.15-13.15 - ven 7 Maggio, h.10.15-12.15 - mar 11 Maggio, h.11.15-13.15 - ven 14 Maggio, h.10.15-12.15 - mar 18 Maggio, h.11.15-13.15 - ven 21 Maggio, h.10.15-12.15 - mar 25 Maggio, h.11.15-13.15 - ven 28 Maggio, h.10.15-12.15 Il corso è rivolto agli studenti della Laurea Magistrale ma la partecipazione è aperta a tutti gli interessati. Chi fosse interessato, può contattarmi privatamente (elvira.dinardo(a)unito.it) per essere incluso nella lista dei partecipanti e ricevere il collegamento Webex. Cordiali saluti, Elvira Di Nardo -- %------------------------------------------------------- Elvira Di Nardo Dept. Mathematics "G. Peano" University of Torino Via Carlo Alberto 10 10123 Torino, Italia tel. +39 0116702862 fax +39 0116702878 http://www.elviradinardo.it %-------------------------------------------------------

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IMPORTANT: Seminar announcement - Petter Kolm (April 28 at 4 pm) CANCELLED
by Giulia Livieri 28 Apr '21

28 Apr '21

Dear all, We are very sorry for the short notice. Unfortunately, we have to postpone — the date will be communicated soon — the seminar of today for a last-minute setback of the speakers; He is really sorry for this. We will communicate the new date for the latter by Petter Kolm soon. Sorry again, Best, Giulia

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Fwd: [owps] talks tomorrow april 29
by Faggionato, Alessandra 28 Apr '21

28 Apr '21

Buongiorno, giro l'annuncio del OWPS per chi fosse interessato. Saluti Alessandra ---------- Forwarded message --------- Da: One World Probability <ow.probability(a)gmail.com> Date: mer 28 apr 2021 alle ore 14:04 Subject: [owps] talks tomorrow april 29 To: <owps(a)lists.bath.ac.uk> Dear All, we have two talks tomorrow. Remember that we start 14:00 UTC which is 16:00 CET! 14:00-15:00 UTC Bastien Mallein Tail behaviour of the derivative martingale in a branching random walk A branching random walk is a discrete-time particle system on the real line in which every particle gives independently birth to offspring positioned around the position of their parent. The derivative martingale of the branching random walk is a stochastic process which allows to measure the number of particles traveling at maximal speed in this process. Under some general integrability conditions uncovered by Aïdékon (2013) and Chen (2015), we know the derivative martingale converges a.s. to a non-negative limit. Recently, Maillard and Pain (2019) obtained a necessary and sufficient condition on the reproduction law of the branching Brownian motion under which the convergence of the derivative martingale satisfies a specific central limit theorem. In this talk, based on a joint work with Alexander Iksanov and Dariusz Buraczewski, we extend their result to branching random walk settings. The proof is based on the characterization of subharmonic functions of the killed random walk with at most linear growth. 15:00 - 16:00 UTC Hui He Deviation probabilities for the maximum of a branching random walk. Consider a supercritical branching random walk on real line started from the origin. Under some mild conditions, it is proved by Aïdékon (2013) that its centered maximum converges in law. In this talk, we will review some recent results on the large/lower deviation probabilities of the maximum. The talk is based on joint works with Xinxin Chen and Bastien Mallein. The Zoom link is on the OWPS webpage. It can also be accessed directly via https://tum-conf.zoom.us/j/66226509320 <https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftum-conf.…> Meeting-ID: 662 2650 9320 Kenncode: 710554 We hope to see you tomorrow! Best wishes, Julien and Nina ID: 662 2650 932 -- ************************************************* Prof. Alessandra Faggionato http://www1.mat.uniroma1.it/~faggionato/ Department of Mathematics University "La Sapienza" Piazzale Aldo Moro, 5 00185 - Rome Office 5, Phone (0039) 06 49913252 *************************************************

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Seminar Aernout van Enter
by Massimo Campanino 28 Apr '21

28 Apr '21

Aernout van Enter ONE-SIDED VERSUS TWO-SIDED STOCHASTIC PROCESSES Thursday the 6th of May 3 pm (Italian time) Stochastic processes can be parametrised by time (such as occurs in Markov chains), in which case conditioning is one-sided (on the past) or by one-dimensional space (which is the case, for example, for one-dimensional Markov fields), where conditioning is two-sided (on the right and on the left). I will discuss some examples, in particular generalising this distinction to g-measures versus Gibbs measures, where, instead of a Markovian dependence, the weaker property of continuity (in the product topology) is considered. In particular I will discuss when the two descriptions (one-sided or two-sided) produce the same objects and when they are different. We show moreover the role one-dimensional entropic repulsion plays in this setting. Based on joint work with R. Bissacot, E. Endo and A. Le Ny, and S. Shlosman ________________________________ Zoom link https://unibo.zoom.us/s/98736182682?zak=eyJ6bV9za20iOiJ6bV9vMm0iLCJhbGciOiJ… Join our Cloud HD Video Meeting<https://unibo.zoom.us/s/98736182682?zak=eyJ6bV9za20iOiJ6bV9vMm0iLCJhbGciOiJ…> Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars across mobile, desktop, and room systems. Zoom Rooms is the original software-based conference room solution used around the world in board, conference, huddle, and training rooms, as well as executive offices and classrooms. Founded in 2011, Zoom helps businesses and organizations bring their teams together in a frictionless environment to get more done. Zoom is a publicly traded company headquartered in San Jose, CA. unibo.zoom.us

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Padova Online Seminar by Gioia Carinci (Università di Modena e Reggio Emilia) [Friday, May 7 at 14.30]
by alessandra bianchi 28 Apr '21

28 Apr '21

Dear Colleagues, We would like to invite you to the following Probability seminar that will take place on May 7 at 14.30 by the zoom platform. ________________________________________________________ Speaker: Gioia Carinci (Università di Modena e Reggio Emilia) Title: Condensation of SIP particles and sticky Brownian motion 7 MAY (Friday) - 14:30 zoom link: TBA available on the webpage https://www.math.unipd.it/~bianchi/seminari/ ) Abstract: The symmetric inclusion process (SIP) is a particle system with attractive interaction. We study its behavior in the condensation regime attained for large values of the attraction intensity. Using Mosco convergence of Dirichlet forms, we prove convergence to sticky Brownian motion for the distance of two SIP particles. We use this result to obtain, via duality, an explicit scaling for the variance of the density field in this regime, for the SIP initially started from a homogeneous product measure. This provides relevant new information on the coarsening dynamics of condensing particle systems on the infinite lattice. Joint works with M. Ayala, C Giardina and F. Redig -- Alessandra Bianchi Dip. di Matematica Università di Padova Via Trieste, 63 - 35121 Padova, Italy phone: +39 049 827 14 06 fax: +39 049 827 14 28 e-mail: bianchi(a)math.unipd.it http://www.math.unipd.it/~bianchi/

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webinars PRISMA Biagini-Colaneri
by c.ceci＠unich.it 26 Apr '21

26 Apr '21

Buongiorno a tutti, abbiamo il piacere di annunciare il quarto appuntamento del ciclo di seminari online promosso dal Gruppo UMI PRISMA. May 3,2021 - 16:00-17:00 (CET) Francesca Biagini Reduced-form setting under model uncertainty with non-linear affine Intensities. - 17:00-18:00 (CET) Katia Colaneri Classical solutions of the Backward PIDE for Markov modulated Marked Point Processes and applications to catastrophic bonds. Abstract Francesca Biagini: In this talk we present a market model including financial assets and life insurance liabilities within a reduced-form framework under model uncertainty by following [1]. In particular we extend this framework to include mortality intensities following an affine process under parameter uncertainty, as defined in [2].This allows both to introduce the definition of a longevity bond under model uncertainty in a consistent way with the classical case under one prior, as well as to compute it by explicit formulas or by numerical methods. We also study conditions to guarantee the existence of a càdlàg modification for the longevity bond’s value process. Furthermore, we show how the resulting market model extended with the longevity bond is arbitrage-free and study arbitrage-free pricing of contingent claims or life insurance liabilities in this setting. This talk is based on: [1] Francesca Biagini and Yinglin Zhang. Reduced-form framework under model uncertainty. The Annals of Applied Probability, 29(4):2481–2522, 2019. [2] Francesca Biagini and Katharina Oberpriller. Reduced-form framework under model uncertainty. Preprint University of Munich and Gran Sasso Science Institute, 2020. [3] Tolulope Fadina, Ariel Neufeld, and Thorsten Schmidt. Affine processes under parameter uncertainty. Probability, Uncertainty and Quantitative Risk <https://link.springer.com/journal/41546> volume 4 (5), 2019. Abstract Katia Colaneri: We give conditions ensuring that the backward partial integro differential equation (PIDE) associated with a multidimensional jump-diffusion with a pure jump component has a unique classical solution. Our proof uses a probabilistic arguments and extends the results of (Pham 1998) to processes with a pure jump component where the jump intensity is modulated by a diffusion process. This result is particularly useful in some applications to pricing and hedging of financial and actuarial instruments, and we provide an example to pricing of catastrophic (CAT) bonds. Collegamento Teams: https://teams.microsoft.com/l/meetup-join/19%3ad685b25ed15f4821ac5168e63cf9… Tutte le informazioni le trovate anche alla pagina http://www.umi-prisma.polito.it/webinars.html Grazie per l’attenzione, Claudia Ceci e Domenico Marinucci ******************************************** Claudia Ceci Dipartimento di Economia Universita' "G. d'Annunzio" di Chieti-Pescara V.le Pindaro 42 65127, Pescara, ITALY c.ceci(a)unich.it *******************************************

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Seminar announcement - Petter Kolm (April 28 at 4 pm)
by Fabrizio Lillo 25 Apr '21

25 Apr '21

*Wednesday April 28 at 4pm (CEST):* Petter Kolm (NYU, Courant Institute) *Title*: Feature Selection in Jump Models *Abstract*: Jump models switch infrequently between states to fit a sequence of data while taking the ordering of the data into account. In this talk, we propose a new framework for joint feature selection, parameter and state-sequence estimation in jump models. Feature selection is necessary in high-dimensional settings where the number of features is large compared to the number of observations and the underlying states differ only with respect to a subset of the features. We develop and implement a coordinate descent algorithm that alternates between selecting the features and estimating the model parameters and state sequence, which scales to large data sets with large numbers of (noisy) features. We demonstrate the usefulness of the proposed framework by comparing it with a number of other methods on both simulated and real data in the form of financial returns, protein sequences, and text. The resulting sparse jump model outperforms all other methods considered and is remarkably robust to noise. This is joint work with Erik Lindstrom and Peter Nystrup The link for joining the meeting is: https://teams.microsoft.com/l/meetup-join/19%3ameeting_NjVmYWI3OTMtZWZkYy00… Best regards Fabrizio Lillo ---------------------------------------- Fabrizio Lillo Dipartimento di Matematica, Università di Bologna Scuola Normale Superiore, Pisa ITALY Personal website: fabriziolillo.wordpress.com University website: www.unibo.it/sitoweb/fabrizio.lillo <http://fabriziolillo.wordpress.com/> phone: +39 050509159

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Seminar announcement
by Marco Scarsini 23 Apr '21

23 Apr '21

Thursday, 29 April, 17:00 CEST *Carri Chan,* Columbia University Prediction-Driven Surge Planning with Applications in the Emergency Department <http://mailsender.luiss.it/lists/lt.php?id=cRpQBwwLSAULAAdOVgFdBQs> Optimizing emergency department (ED) nurse staffing decisions to balance the quality of service and staffing cost can be extremely challenging, especially when there is a high level of uncertainty in patient-demand. Increasing data availability and continuing advancements in predictive analytics provide an opportunity to mitigate demand-rate uncertainty by utilizing demand forecasts. In this work, we study a two-stage prediction framework that is synchronized with the base (made months in advance) and surge (made nearly real-time) staffing decisions in the ED. We quantify the benefit of the more expensive surge staffing. We also propose a near-optimal two-stage staffing policy that is straightforward to interpret and implement. Lastly, we develop a unified framework that combines parameter estimation, real-time demand forecasts, and staffing in the ED. High fidelity ED simulation experiments demonstrate that the proposed framework can reduce staffing costs by 8% – 17% while guaranteeing timely access to care. Joint work with Jing Dong and Yue Hu. Discussants: Vahid Sarhangian and Julien Grand-Clément This is the link to the Virtual Room <http://mailsender.luiss.it/lists/lt.php?id=cRpQAAYBSAULAAdOVgFdBQs>. If you want to receive the password to access the virtual room, please fill out this form <https://docs.google.com/forms/d/e/1FAIpQLSeDxM-M5ogG43elgjC-lNCp0BDhISiZHG0…> (If you filled it out in the past, this is not necessary). The schedule of the upcoming seminars can be found here <https://economiaefinanza.luiss.it/en/seminars/2020-2021-seminars>. ******************************************************* Marco Scarsini Dipartimento di Economia e Finanza Luiss Viale Romania 32 00197 Roma, ITALY URL: http://docenti.luiss.it/scarsini/

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